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Exporting matplotlib plot to holoviews

I'm using a library called GPy to fit a Gaussian process model and plot the output. The library has it's own plotting functionality, and returns a matplotlib figure.
I'd like to use this output in a holoviews element, as part of a dynamic map. This feels like it should be possible, but I can't find a good way to do it.
I had wondered about reading the matplotlib figure into a numpy image array and sending this to a holoviews Raster element - but the only way to do this seems to be saving the figure to a file, which does not seem a good option.

Great question! At the point where you define holoviews elements, they are still backend-agnostic. Matplotlib etc. only come into play when they are actually rendered. Hence no, you cannot take a matplotlib figure as such and pipe that into a holoviews element.
Hence you have two options:
Extract the data from the matplotlib figure in some way, or get hold of those data from GPy in some other way, and create a holoviews element from that, or
Use the code that generates the matplotlib figure in a panel (https://panel.pyviz.org) app.
Number 2 is closer to what you are probably imagining but without a minimal working example I cannot say much more.

Matplotlib animated plot as data is aquired

I have a script that produces real time data, is it possible to plot all of this data and show a moving curve as data is acquired using matplotlib?

Matplotlib supports animations. The easiest is to look at some of the examples.

Animate 3D plotting data using Mayavi in Python

I have an array of points (x,y,z) that I would like to animate in 3D using Mayavi (Python). I am currently using a Plot3D command to plot all of the points simultaneously (modeling the movement of a particle), but would love some help on the animation.
Thanks!

Matplotlib offers a lot of possibilities for animation. Have a look at the specific routines for animation. In particular, there's a specific example for 3D plotting.
There are quite a few tutorials on the 'web. Eg. Matplotlib Animation Tutorial and Animated 3-D Plots in Python

graphing a relationship matrix in python

i have a python interface using wxpython which allows the user to fill in a matrix (0/1) and then graphs it for them. The program creates a numpy matrix, then makes a networkx graph out of that matrix, and then uses matplotlib.pylab to display the graph.
numpy is a must, because the program also does other things like get the transitive, reflexive, and symmetric closures... as for networkx i can use something else if u recommend something else better for graphing matrices, and as for matplotlib, i hate it, please if u know of any other way to display a graph please advice.
matplotlib is the source of my problem, when the users clicks the graph button, my programs reads the matrix, makes a graphs and matplotlib displays it in a new window (by default). Now if the users goes back to the original window and graphs a different matrix without first closing the matplotlib window, the program crashes.
also the way the relationship "arrows" are drawn is, in my opinion, unattractive.
i need a better way to graph my matrix, or at the very least as a way to force close the myplotlib window, i tried plt.close() but that didnt work, the window would remain open, and both windows will say (Not Responding) and i have to end process.
this is the part of the code in question:
import numpy as np
import networkx as nx
import matplotlib.pylab as plt
...
...
...
def graph(values)
plt.close() #with or without this it does not work
matrix = np.matrix(values)
graph = nx.DiGraph(matrix)
nx.draw(graph)
plt.show()
return

It seems to me like your main complaint is in the way that wx handles the matplotlib windows. It is possible to embed the Matplotlib figure in your wx window. Here's an example:
http://wiki.scipy.org/Matplotlib_figure_in_a_wx_panel (updated)
It gets a bit complicated. Basically, you should copy the code and replace the "DemoPlotPanel.draw()" method. You'll need to modify your code to specify the axis to draw on. It's buried in the networkx documentation here:
http://networkx.lanl.gov/reference/drawing.html

I am just using an example of the Networkx documentation:
try:
import matplotlib.pyplot as plt
except:
raise
import networkx as nx
G=nx.star_graph(20)
pos=nx.spring_layout(G)
nx.draw(G,pos)
plt.show() # display
So your plt.close() statement at the start does not make sense, you should remove it.You should also calculate the coordinates for your nodes, the sentence pos=nx.spring_layout(G) does this. You call a specific layout algorithm and supply your graph G, you get a dictionary in return with for each node the x and y coordinates.
Have a close look at the examples at: http://networkx.lanl.gov/gallery.html

How can I duplicate this simple matlab plot functionality with mathplotlib?

Here is a simple matlab script to read a csv file, and generate a plot (with which I can zoom in with the mouse as I desire). I would like to see an example of how this is done in python and mathplotlib.
data = csvread('foo.csv'); % read csv data into vector 'data'
figure; % create figure
plot (data, 'b'); % plot the data in blue
In general, the examples in mathplotlib tutorials I've seen will create a static graph, but it's not interactively "zoomable". Would any python expert care to share an equivalent?
Thanks

import matplotlib.pyplot as plt
import numpy as np
arr=np.genfromtxt('foo.csv',delimiter=',')
plt.plot(arr[:,0],arr[:,1],'b-')
plt.show()
on this data (foo.csv):
1,2
2,4
3,9
produces
When you setup the matplotlibrc, one of the key parameters you need to set is the backend. Which backend you choose depends on your OS and installation.
For any typical OS there should be a backend that allows you to pan and zoom the plot interactively. (GtkAgg works on Ubuntu). The buttons highlighted in red allow you to pan and zoom, respectively.

Since you're familiar with Matlab, I'd suggest using the pylab interface to matplotlib - it mostly mimics Matlab's plotting. As unutbu says, the zoomability of the plot is determined by the backend you use, a separate issue.
from pylab import *
data = genfromtxt("file.csv")
plot(data, 'b')